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This study aims to empirically study the effect of process constraints and the combinative effects of different constraints on enterprise digital transformation.

This paper selects the World Bank's business environment survey of Chinese enterprises in 2012 as the research sample to empirically study the effect of process constraints and different kinds of constraints on enterprise digital transformation.

The authors find that process constraints have an inverted U-shaped effect on enterprise digital transformation and that employee digital literacy plays an intermediary role in this process. That is, process constraints have a too-much-of-a-good-thing effect on employees' digital literacy, which further affects enterprise digital transformation. The increase in the number of input and output constraints will make the inverted U-shaped relationship between the process constraint and digital transformation steeper.

The constraints faced by enterprises are everywhere and of many kinds. This paper not only discusses the influence of process constraints on enterprise digital transformation but also analyzes the interactive influence of different kinds of constraints on enterprise digital transformation and explores its micromechanism. This approach is helpful for enterprise managers in thinking about how to make full use of different kinds of constraints to activate the power of enterprise digital transformation, regard constraints as challenges and opportunities, and use them to stimulate the ability to improve the resource integration and utilization.

The purpose of this paper is to present a comprehensive descriptive analysis of the sequential application of the Theory of Constraints (TOC) five‐step focusing process in improving the effectiveness of a service process that was limiting the performance of the entire service system.

The five‐step approach is schematically presented with each step being described and evaluated relative to its role in effective constraint management. A detailed example provides additional insights and nuances into its use in managing the constraint within a banking organization's subsystem, namely, the loan application and approval process. This hypothetical, realistic, and comprehensive illustration iterates through several cycles of the five‐step focusing process to demonstrate how managers are able to address different types of constraints.

The paper provides a detailed description on how each of the five‐steps can be used to improve the organization's performance relative to its stated goal by focusing management's attention on the system's (or an aligned subsystem's) leverage or control point. Major types of constraints include physical or capacity limitations and restrictive policies. Constraints may be located either internal or external to the process or system being managed.

Various managerial implications are discussed including: the relevance and utility of applying the TOC five‐step focusing process in services; advantages associated with utilizing this structured approach for continuous improvement in services; and some strategic issues associated with the placement of the ubiquitous system constraint.

Although the successful application of the five‐step focusing process has been well documented in improving manufacturing processes, this paper provides an illustrative tutorial which details its application in effectively managing a service process.

This paper presents M-PoP, a method to model large, complex, and dynamic business processes. These processes have sometimes resulted from alliances of organizations (i.e. joint ventures and mergers and acquisitions) and are referred to as Processes-of-Business Processes (PoP). Due to the difficulty of modeling these dynamic processes, alliances of organizations have often lost opportunities, competitiveness, and profitability, so requiring suitable modeling methods.

The authors proposed M-PoP that can model PoP through three views in different abstraction levels and using well-known techniques in industry and academia, mainly those from Business Process Model and Notation (BPMN). For this, M-PoP presents three main steps: identification of PoP elements, modeling of PoP, and verification of PoP models. To evaluate M-PoP, we applied it in a real-world business process in the health domain.

The evaluation results point out the capability and viability of M-PoP to deal with dynamic business processes.

M-PoP still needs to be applied in various real-world scenarios to gather evidence of its productivity, efficiency, and scalability.

This novel method could change the way organizations model their business processes and, as a consequence, it could leverage strategic business opportunities.

M-PoP is the first method that makes it possible to model large and complex business processes and, most importantly, dynamic processes.

The purpose of this paper is to present a methodology for extracting innovation constraints from building projects through stakeholder management competencies and failure mode and effect analysis (FMEA).

The methodology was an iterative grounded theory process using case studies. A literature‐based concept model was generated which mapped project procurement stages against the innovation process. Constraints and stakeholder management strategies were extracted from 30 case studies using content analysis and mapped against the procurement stages. FMEA was used to evaluate the criticality of the constraints. For the purposes of this paper, a sample case study was detailed and referred to as the pilot study. The m\ethodology was applied to all the case studies and a schedule of constraints (SoC) extracted.

This paper evidenced that it is not project constraints which require management to sustain innovation but rather failures in stakeholder competency. This study established the benefits of FMEA as a risk assessment tool for construction innovation research and generated a database of innovation constraints which can be used as a benchmarking framework for future research.

Previous construction innovation research has focused on established project management techniques to manage innovation. This study identified that rather than a process‐driven approach, a stakeholder‐centred approach is required, where successful innovation delivery is incumbent on the right stakeholder competencies being in place at the appropriate stages of the procurement process. The benefit of this contribution is an established risk assessment methodology which can be used by project stakeholders when adopting innovation into construction projects.

As a critical component in the entrepreneurial process, knowledge is essential to the study of how entrepreneurs compete under constraints. Research in this area is challenged by the unobservable and imprecise nature of knowledge which inhibits advanced theory building and testing, and we explore this problem by analyzing the relationship between the entrepreneurial process, constraints to the process, and knowledge flows. We apply and extend a systems-theoretic framework that identifies the knowledge system in entrepreneurial organizations, and develop an integrative model to guide future research.

This paper proposes an innovative intelligent simulation-based construction planning framework that introduces a new approach to simulation-based construction planning.

In this approach, the authors developed an ontological inference engine as an integrated part of a constraint-based simulation system that configures the construction processes, defines activities and manages resources considering a variety of requirements and constraints during the simulation. It allows for the incorporation of the latest project information and a deep level of construction planning knowledge in the planning. The construction planning knowledge is represented by an ontology and several semantic rules. Also, the proposed framework uses the project building information model (BIM) to extract information regarding the construction product and the relations between elements. The extracted information is then converted to an ontological format to be useable by the framework.

The authors implemented the framework in a case study project and tested its usefulness and capabilities. It successfully generated the construction processes, activities and required resources based on the construction product, available resources and the planning rules. It also allowed for a variety of analyses regarding different construction strategies and resource planning. Moreover, 4D BIM models that provide a very good understanding of the construction plan can be automatically generated using the proposed framework.

The active integration between BIM, discrete-event simulation (DES) and ontological knowledge base and inference engine defines a new class of construction simulation with expandable applications.

Business ethics provide a potent source of competitive advantage, placing increasing pressure on organizations to create and maintain an ethical workforce. Nonetheless, ethical breaches continue to permeate corporate life, suggesting that there is something missing from how we conceptualize and institutionalize organizational ethics. The current effort seeks to fill this void in two ways. First, we introduce an extended ethical framework premised on sensemaking in organizations. Within this framework, we suggest that multiple individual, organizational, and societal factors may differentially influence the ethical sensemaking process. Second, we contend that human resource management plays a central role in sustaining workplace ethics and explore the strategies through which human resource personnel can work to foster an ethical culture and spearhead ethics initiatives. Future research directions applicable to scholars in both the ethics and human resources domains are provided.

The general principles of TOC can be applied to improve the performance of service organizations. A classified model is proposed for such applications based on Schmenner’s classification of service organizations. The flow of “material”, inventory and throughput is identified at various service organizations of the four quadrants of the service matrix. The definition of these terms might be dependent on the service. Since system constraint is at the heart of TOC, the recognition of the nature of organization constraint is the first step towards continuous improvement.

In response to the challenge of reduced efficiency or failure of robot motion planning algorithms when faced with end-effector constraints, this study aims to propose a new constraint method to improve the performance of the sampling-based planner.

In this work, a constraint method (TC method) based on the idea of cross-sampling is proposed. This method uses the tangent space in the workspace to approximate the constrained manifold pattern and projects the entire sampling process into the workspace for constraint correction. This method avoids the need for extensive computational work involving multiple iterations of the Jacobi inverse matrix in the configuration space and retains the sampling properties of the sampling-based algorithm.

Simulation results demonstrate that the performance of the planner when using the TC method under the end-effector constraint surpasses that of other methods. Physical experiments further confirm that the TC-Planner does not cause excessive constraint errors that might lead to task failure. Moreover, field tests conducted on robots underscore the effectiveness of the TC-Planner, and its excellent performance, thereby advancing the autonomy of robots in power-line connection tasks.

This paper proposes a new constraint method combined with the rapid-exploring random trees algorithm to generate collision-free trajectories that satisfy the constraints for a high-dimensional robotic system under end-effector constraints. In a series of simulation and experimental tests, the planner using the TC method under end-effector constraints efficiently performs. Tests on a power distribution live-line operation robot also show that the TC method can greatly aid the robot in completing operation tasks with end-effector constraints. This helps robots to perform tasks with complex end-effector constraints such as grinding and welding more efficiently and autonomously.

Buffers of work throughout a manufacturing facility enhance throughput. They protect a workstation against variations in processing times and against machine breakdowns of upstream workstations. However, buffer management is still thought to be an open problem: first there is no algebraic way of representing the relationship between buffer size and throughput, and second, the combinatorial nature inherent in the buffer design problem makes it difficult to develop an exact solution. These problems still exist today, as evidenced by the number of research papers that present sophisticated mathematics to solve this complex problem. Refutes all the above points. The buffer management method detailed does not use sophisticated mathematics impenetrable by the average production manager. Presents a heuristically‐based buffer management method effective at protecting throughput. The method will have advantageous effects on the size of buffers and the length of the production lead times, while still providing protection of the throughput rate.